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management. Artificial Intelligence & Machine Learning: Predictive risk modeling for falls, hospitalization, and cognitive decline; Natural Language Processing (NLP) for remote cognitive assessment; image
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condition. Her lab uses spatial statistical models, geographic information system tools, bioinformatics, and artificial intelligence to predict communities most at risk for existing and emerging infectious
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to understand deformation-controlled hydrogen systems by integrating seismic observations and THMC physical modeling at three complementary sites: Comminges (primary target), Oman, and New Caledonia. The central
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 days ago
, CNRS, INRAE, INSERM …), but also with the regional economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and
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truth" data for satellite remote sensing (Sentinel) and biogeochemical predictive models (e.g., RothC, Agricolus DSS). Living Lab Management & Co-creation: Act as the primary local contact for farmers
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mathematical foundations needed to make deep operators reliable, robust, and applicable for control of complex engineering systems. In this PhD project, you will investigate how operator-learning models can
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: to develop next-generation autonomous crop monitoring and decision-support systems for Controlled Environment Agriculture. By integrating plant sensing, data and crop models, we aim to enable more precise and
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, and Posit Connect for deploying dashboards and predictive models that support the University's fundraising campaigns. This position reports directly to the Senior Director of Advancement Analytics in
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localization and navigation. Experience in one or more of the following: path planning, motion planning, trajectory optimization or model predictive control; reinforcement learning, imitation learning
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frameworks to understand, predict, and control tissue-scale dynamics by integrating mechanistic and data-driven approaches across molecular, cellular, and tissue scales. Particular interest will be given